Garrett Burhenn — OGILVIE

Garrett Burhenn P Erie SeaWolves

Age 26 RHP 6'3" / 215 lbs AA Svc 0.0 · Ctrl thru 2034 peak 1.0 · 2027

2026 ROS PROJECTION0 act + 1 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 123115vR 106

ERA4.71

FIP4.71

K%16.5%

BB%7.2%

K-BB%9.3%

ROS IP1

Value2026 · WAR

Runs saved vs league avg · 1 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit-$0M ctrl surplus

Grades · Contract

Scouting Grades

STUF4040

CTRL6060

CMD5050

K†4040

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status MiLB

MLB Debut 2029

Service 0 yrs (est)

Team Control Through 2034

First FA Year 2035

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2029
2027	MiLB	still in minors · estimated debut 2029
2028	MiLB	still in minors · estimated debut 2029
2029	Pre-Arb	$0.8M	—	—	—
2030	Pre-Arb	$0.9M	—	—	—
2031	Ext	beyond projection horizon · no WAR estimate
2032	Ext	beyond projection horizon · no WAR estimate
2033	Ext	beyond projection horizon · no WAR estimate
2034	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$-0.3M	+$0.0M

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral

Methodology▸ how WAR & MLE are computed

Stats are park-neutral MLB equivalents. The "TEAM" column shows current org affiliation only — we do NOT project at that team's park.
Rates (K%, BB%, HR-BF) are park-stripped; MiLB stat lines are translated to their MLB-equivalent via per-level MLE factors.
WAR is computed from projected runs prevented vs a replacement pitcher (the marginal arm a team would call up if this pitcher were unavailable) — calibrated to industry-standard fWAR.

Year	Age	Lvl	Team	G	GS	IP	BF	K	BB	HR	GS%	IP/G	K%	BB%	K-BB%	HR%	ERA	FIP	WAR
▸ Career — actual stats, one row per year (as recorded, no adjustments)
▸ Career — adjusted (each season translated to a park/league-neutral MLB-equivalent line; levels combined per year)
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
2022	22	MIX MLE	2 levels	22	20	92	395	112	26	14	91%	4.2	21.1%	7.7%	13.3%	3.8%	4.01	4.40	—
2022	22	MIX RAW	2 levels	22	20	92	395	112	26	14	91%	4.2	28.4%	6.6%	21.8%	3.5%	4.01	3.49	—
2023	23	A+ MLE	West Michigan Whitecaps	24	18	94	398	70	29	7	75%	3.9	13.5%	8.4%	5.2%	2.5%	4.04	4.39	—
2023	23	A+ MLE	West Michigan Whitecaps	24	18	94	398	70	29	7	75%	3.9	13.5%	8.4%	5.2%	2.5%	4.04	4.39	—
2023	23	A+ RAW	West Michigan Whitecaps	24	18	94	398	70	29	7	75%	3.9	17.6%	7.3%	10.3%	1.8%	4.04	3.51	—
2024	24	MIX MLE	2 levels	27	26	122	518	123	42	13	96%	4.5	19.0%	9.0%	10.0%	3.3%	3.68	4.42	—
2024	24	MIX MLE	2 levels	27	26	122	518	123	42	13	96%	4.5	19.0%	9.0%	10.0%	3.3%	3.68	4.42	—
2024	24	MIX RAW	2 levels	27	26	122	518	123	42	13	96%	4.5	23.7%	8.1%	15.6%	2.5%	3.68	3.50	—
2025	25	AA MLE	Erie SeaWolves	26	24	125	523	112	33	15	92%	4.8	17.3%	6.9%	10.4%	3.3%	4.18	4.30	—
2025	25	AA MLE	Erie SeaWolves	26	24	125	523	112	33	15	92%	4.8	17.3%	6.9%	10.4%	3.3%	4.18	4.30	—
2025	25	AA RAW	Erie SeaWolves	26	24	125	523	112	33	15	92%	4.8	21.4%	6.3%	15.1%	2.9%	4.18	3.66	—
▸ 2026 season — projected remainder (no 2026 stats recorded)
2026	26	MLB	DET	1	1	1	4	1	0	0	100%	1.0	16.5%	7.2%	9.3%	3.1%	4.71	4.71	+0.0
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	27	MLB MLE	DET	18	18	111	468	80	34	15	100%	6.2	17.0%	7.4%	9.7%	3.2%	4.69	4.71	+0.2
2028	28	MLB MLE	DET	18	18	108	454	78	34	15	100%	6.0	17.3%	7.5%	9.8%	3.2%	4.71	4.76	+0.2
2029	29	MLB MLE	DET	17	17	103	434	75	34	15	100%	6.0	17.3%	7.8%	9.5%	3.4%	4.79	4.86	+0.0
2030	30	MLB MLE	DET	16	16	96	407	70	33	15	100%	6.0	17.1%	8.1%	9.0%	3.6%	4.92	5.02	-0.1
2027	27	MLB CTX	DET	7	7	42	177	30	13	5	100%	6.0	17.0%	7.4%	9.7%	3.0%	4.62	4.64	+0.1
2028	28	MLB CTX	DET	11	11	64	270	47	20	8	100%	5.8	17.3%	7.5%	9.8%	3.1%	4.63	4.68	+0.1
2029	29	MLB CTX	DET	12	12	73	308	53	24	10	100%	6.1	17.3%	7.8%	9.5%	3.2%	4.71	4.78	+0.0
2030	30	MLB CTX	DET	13	13	76	321	55	26	11	100%	5.8	17.1%	8.1%	9.0%	3.4%	4.84	4.94	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		42	42	254	1072	184	83	35	100%	6.0	17.2%	7.7%	9.4%	3.2%	4.71	4.40	+1.5
/ 200 IP	—	RAW		33	33	200	844	145	65	28	100%	6.0	17.2%	7.7%	9.4%	3.2%	4.71	4.40	+1.2
Career	—	MLE		99	88	433	1834	326	147	59	89%	4.4	17.8%	8.0%	9.8%	3.2%	3.97	4.37	+0.3
/ 200 IP	—	MLE		46	41	200	847	151	68	27	89%	4.4	17.8%	8.0%	9.8%	3.2%	3.97	4.37	+0.2

Career Path Comps

What happened to similar pitchers from this age · Y-axis: ERA+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

			Profile at Match Age					Next 3 Yrs				Career
Comp	Age	Role	FIP	K%	BB%	HR/BF	BABIP	FIP	K%	K-BB%	IP	ΔFIP	Low FIP	IP	Match
Garrett Burhenn (OGILVIE)	—	—	4.71	16.5%	7.2%	3.1%	—	4.77	17.2%	9.7%	321	+0.06	—	—	—
Nestor Molina R 2016 · 4.83 FIP	27	SP	4.83	15.0%	8.0%	3.6%	.304	3.61	17.0%	10.2%	289	-1.22	3.01	401	86
Connor Noland R 2023 · 3.98 FIP	24	SP	3.98	14.8%	5.7%	2.6%	.290	4.32	15.8%	8.2%	335	+0.34	3.98	443	86
Shane Greene R 2015 · 4.50 FIP	26	SP	4.50	13.0%	6.6%	3.0%	.309	3.60	24.1%	15.6%	191	-0.90	2.86	484	84
David Phelps R 2015 · 3.94 FIP	28	SP	3.94	16.0%	6.8%	2.4%	.299	2.82	29.9%	20.6%	142	-1.12	2.50	373	84
Cameron Foster R 2023 · 4.31 FIP	24	SP	4.31	18.9%	10.3%	2.7%	.329	4.05	20.9%	10.9%	132	-0.26	2.54	213	84
Markus Solbach R 2019 · 3.58 FIP	27	SP	3.58	16.9%	6.1%	2.1%	.311	4.62	17.1%	9.1%	111	+1.04	3.34	391	83
Hector Noesí R 2015 · 4.37 FIP	28	SP-	4.37	17.6%	8.1%	3.2%	.261	—	—	—	—	—	4.37	250	83
David Hale R 2015 · 4.15 FIP	27	SP-	4.15	16.2%	6.8%	2.8%	.343	4.11	13.8%	8.1%	251	-0.04	3.30	493	82
Marcelo Perez R 2023 · 3.84 FIP	23	SP	3.84	18.0%	8.6%	2.1%	.288	4.99	14.7%	7.3%	238	+1.15	3.84	306	82
Jason Forjet R 2016 · 4.48 FIP	26	SP	4.48	15.9%	5.5%	3.7%	.260	—	—	—	—	—	3.36	197	81
Brandon Birdsell R 2023 · 3.91 FIP	23	SP	3.91	17.1%	8.3%	2.2%	.266	4.05	19.2%	13.6%	154	+0.14	3.87	262	81
Caleb Kilian R 2023 · 4.66 FIP	26	SP	4.66	15.4%	6.2%	3.8%	.290	3.57	21.4%	13.2%	105	-1.09	2.42	444	81
Jared Mortensen R 2015 · 4.42 FIP	27	SP-	4.42	16.9%	7.8%	3.2%	.287	4.99	20.9%	2.1%	72	+0.57	4.42	200	81
Allen Webster R 2015 · 5.05 FIP	25	SP	5.05	14.0%	9.1%	3.6%	.356	5.78	14.9%	6.8%	58	+0.73	4.56	177	80
Hector Velázquez R 2015 · 4.31 FIP	26	SP	4.31	15.0%	8.7%	2.5%	.297	3.35	18.1%	12.8%	343	-0.96	2.75	536	80
Joe Wieland R 2016 · 4.27 FIP	26	SP	4.27	18.6%	7.3%	3.3%	.359	—	—	—	—	—	3.38	270	80
Andrew Quezada R 2023 · 5.33 FIP	26	SP-	5.33	14.4%	9.5%	4.1%	.344	4.92	12.5%	5.0%	173	-0.41	4.40	412	80
Shawn Haviland R 2015 · 3.95 FIP	29	SP-	3.95	14.6%	6.0%	2.4%	.303	4.67	16.1%	8.8%	169	+0.72	3.69	283	80
Tim Atherton R 2015 · 3.77 FIP	25	SP	3.77	16.2%	8.6%	1.7%	.291	—	—	—	—	—	3.77	101	80
Forrest Snow R 2015 · 5.03 FIP	26	SP-	5.03	16.1%	8.2%	4.1%	.263	4.14	21.8%	14.2%	256	-0.89	3.02	406	80

Career Comps

Retired MLB careers whose totals most resemble what we're projecting for this player. Pool: 133 completed pitcher careers (2015-2024).

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	2.5	100	17.1%	7.6%	1.27	4.76
Daniel Mengden ('19)	1.5	73	17.3%	7.7%	1.24	4.68
Zach Plesac ('23)	2.3	93	18.4%	6.3%	1.39	4.20
Homer Bailey ('19)	1.9	96	18.5%	7.8%	1.34	5.56
Yonny Chirinos ('24)	1.7	84	18.9%	6.6%	1.38	4.37
Matt Manning ('24)	1.3	64	16.4%	7.8%	1.06	4.43
Cole Irvin ('24)	2.9	118	17.1%	5.6%	1.28	4.46